The Importance of Effort and its Impact in Building the Society in the Light of
the Holy Book and Sunna.
Thank for God and peace be upon Prophet Muhammad, His hose hold and
Companions.
This research is to refute a fault : that Islam as a religioncalls for laziness and
dependence and this in first, Second, to show the originality of the Islamic method in
building and construction.
This research Starts with an introduction in which I refer to the nature of the
Islamic method and its way of work in life: that it is a divine method that is achieved
by the effort of the people them selfves and not through a divine extraordinary power:
The research explains the shift in the peoples life who were addressed by this
Quran through the new concepts it presents.
This Holy Quran calls people to work fast, to forego and to compete; it gives
many examples that instigate people to work and it explains to people how man
should move to get the goal he is looking for.
In addition , the sayings of prophet Muhammad –peace be upon him- refer to
the importance of effort and its impact in building the society, These sayings are put
within axes to make the picture clearer and such axes include:
1. Sayings that refer to the importance of work to satisfy mans needs.
2. Sayings that refer to the earth recoustruction and the importance of
implantation.
3. Sayings that guide the Muslim to work for the good.
4. Sayings that call for discarding superstitions, illusions that prevent him from
doing what he intends or plans to do.
In this work, we study a new class of meromorphicmultivalent functions, defined by fractional differ-integral operator.We obtain some geometricproperties, such ascoefficient inequality, growth and distortion bounds, convolution properties, integral representation, radii of starlikeness, convexity, extreme pointsproperties, weighted mean and arithmetic meanproperties.
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A new route of knoevenagel condensation for trans-3-(2-furyl)acroline with Rhodanine, Barbituric acid ,Thiazolidine-2,4-dione and 2-Thiohydantoin,in the presence of cetyltrimethylammoniumbromide(CTMAB) at room temperature in water .
Used cooking oil was undergoing trans-esterification reaction to produce biodiesel fuel. Method of production consisted of pretreatment steps, trans-esterification, separation, washing and drying. Trans-esterification of treated oils was studied at different operation conditions, the methanol to oil mole ratio were 6:1, 8:1, 10:1, and 12:1, at different temperature 30, 40, 50, and 60 º C, reaction time 40, 60, 80, and 120 minutes, amount of catalyst 0.5, 1, 1.5, and 2 wt.% based on oil and mixing speed 400 rpm. The maximum yield of biodiesel was 91.68 wt.% for treated oils obtained by trans-esterification reaction with 10:1 methanol to oil mole ratio, 60 º C reaction temperature, 80 minute reactio
... Show MoreThe fractional free volume (Fh) in polystyrene (PS) as a function of neutron -irradiation dose has been measured, using positron annihilation lifetime (PAL) method. The results show that Fh values decreased with increasing n-irradiation dose up to a total dose of 501.03× 10-2 Gy.
A percentage reduction of 2.14 in Fh values is noticed after the initial n-dose corresponding to a percentage reduction in the free volume equal to 42.14/Gy.
The total n-dose induces a percentage reduction of 7.26, corresponding to a percentage reduction of 1.45/Gy. These results indicate that cross -linking is the predominant process induced by n-irradiation.
The results suggest that n-irradiation induces structure changes in PS, causing cross-linking
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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